Results 81 to 90 of about 1,586 (147)

Exact Solutions of Linear Multiple Delay Partial Differential Equations

Mathematical Methods in the Applied Sciences, Volume 49, Issue 12, Page 14282-14291, August 2026.
ABSTRACT This paper develops an analytical framework for linear differential equations with multiple discrete delays. A new function, referred to as the multiple‐delay exponential function, is introduced, and some of its fundamental properties are established.
Stuart‐James M. Burney
wiley   +1 more source

Physics-Informed Neural Networks with Unknown Partial Differential Equations: An Application in Multivariate Time Series. [PDF]

Entropy (Basel)
Mortezanejad SAF, Wang R, Mohammad-Djafari A.   +2 more
europepmc   +1 more source

Efficient Tensor Completion Algorithms for Highly Oscillatory Operators

Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.
ABSTRACT We address the problem of recovering highly oscillatory operators, represented as n×n$$ n\times n $$ matrices with a fixed set of observed entries. Given that these matrices can be well compressed by butterfly matrix decomposition of L=𝒪(logn) levels requiring only O(nlogn)$$ O\left(n\log n\right) $$ degrees of freedom, we propose a novel ...
Navjot Singh, Edgar Solomonik, Xiaoye Sherry Li, Yang Liu   +3 more
wiley   +1 more source

New analytical wave solutions for the gardner equation via the Riccati-modified extended simple equation method. [PDF]

Sci Rep
Jawarneh Y, Almusawa MY, Haleemzai I, Hakami AH, Ahmadini AAH, Albaity A.   +5 more
europepmc   +1 more source

Synergistic Engineering of Nanostructures via Anodic Aluminum Oxide Templates and Atomic Layer Deposition: Design Principles, Mechanisms, and Applications

Small Structures, Volume 7, Issue 8, August 2026.
Anodic aluminum oxide (AAO) templates combined with atomic layer deposition (ALD) constitute a synergistic platform for engineering functional nanostructures within highly ordered, high‐aspect‐ratio porous architectures. By linking precursor transport modeling, surface chemistry control, and tailored ALD strategies, this review establishes a unified ...
Hyeon Joon Choi, Neul Ha, Jisu Jung, Ryeowon Kim, S. Joon Kwon, Sunghak Park, Wooseok Yang, Hyunjung Shin   +7 more
wiley   +1 more source

NeuberNet: a neural operator solving elastic-plastic partial differential equations at V-notches from low-fidelity elastic simulations. [PDF]

Commun Eng
Grossi T, Beghini M, Benedetti M.
europepmc   +1 more source

Fine‐Tuning a Weather Foundation Model With Lightweight Decoders for Unseen Physical Processes

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Recent advances in AI weather forecasting have led to the emergence of so‐called “foundation models”, typically defined by expensive pretraining and minimal fine‐tuning for downstream tasks. However, in the natural sciences, a desirable foundation model should also encode meaningful statistical relationships between the underlying physical ...
Fanny Lehmann, Firat Ozdemir, Benedikt Soja, Torsten Hoefler, Siddhartha Mishra, Sebastian Schemm   +5 more
wiley   +1 more source

Regression and statistical analysis of heat transfer enhancement in water/ethylene glycol (40/60) base molybdenum carbide (Mo₂C) MXene nanofluid using a transient fractional model. [PDF]

Discov Nano
Sheikh NA, Ismail ZB, Khan I, Elnaggar GR, Teklu SW.   +4 more
europepmc   +1 more source

Numerical Investigation of a Diffusive SIR Model: Focus on Positivity Preservation

Mathematical Methods in the Applied Sciences, Volume 49, Issue 11, Page 11775-11793, 30 July 2026.
ABSTRACT In this paper, we consider a system of semilinear partial differential equations (PDEs) representing a spatially extended SIR epidemic model. A brief analytical investigation of the well‐posedness and positivity of the solutions is provided in the appendix, while the main focus is on the numerical treatment of the model.
Rahele Mosleh, Claudia Panico, Messoud Efendiyev   +2 more
wiley   +1 more source

Partial differential equations in data science. [PDF]

Philos Trans A Math Phys Eng Sci
Bertozzi AL, Drenska N, Latz J, Thorpe M.   +3 more
europepmc   +1 more source